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Monitor brand mentions with OpenAI across Twitter/X, Reddit, News, Airtable and Slack

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Created by: Oneclick AI Squad || oneclick-ai

Oneclick AI Squad

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Last update 3 hours ago

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Monitors brand mentions across Twitter/X, Reddit, and News APIs in real-time (or scheduled), fetches mentions in parallel, normalizes data, uses AI to analyze sentiment/urgency/topics, detects duplicates, filters critical mentions, logs everything to Airtable, posts alerts to Slack, and emails daily HTML digest reports to the marketing team.

Good to Know

  • Runs every hour (configurable) to provide near-real-time brand monitoring
  • Pulls mentions from multiple platforms in parallel: Twitter/X, Reddit, News sources
  • Uses AI (OpenAI/Grok/etc.) for advanced sentiment classification, urgency detection, topic extraction, and duplicate deduplication
  • Focuses on actionable insights: flags negative/urgent mentions for immediate response
  • Generates beautiful HTML daily digest with summarized mentions, sentiment trends, and key highlights
  • Stores historical data in Airtable for tracking, analytics, and long-term reporting
  • Sends real-time Slack alerts for high-priority/negative mentions
  • Reduces manual social monitoring time dramatically and helps catch reputation issues early

How It Works

1. Trigger & configure

  • Schedule Trigger — Runs every hour (or custom interval) to check for new brand mentions
  • Set brand monitoring config — Defines brand name, keywords, excluded terms, monitoring parameters (via Set node or variables)

2. Fetch & collect mentions

  • Fetch Twitter/X mentions — Uses Twitter/X node or HTTP Request to search recent tweets (mentions, keywords)
  • Fetch Reddit mentions — Searches relevant subreddits or Reddit-wide for brand keywords/posts
  • Fetch news article mentions — Queries news APIs (e.g. NewsAPI, Google News via RSS/HTTP) for brand coverage
  • Merge platform mentions — Combines results from all sources into a unified stream
  • Normalize mentions into unified schema — Standardizes fields (text, author, platform, timestamp, URL, etc.) for consistent processing

3. AI analyze & deduplicate

  • AI sentiment and urgency analysis — Sends mentions to AI model (OpenAI node) with prompt to classify:
    • Sentiment: positive / neutral / negative
    • Urgency/severity: low / medium / high / critical
    • Topics/themes
    • Key excerpts
  • Wait For Result — Ensures AI responses are complete
  • Process analysis results — Parses structured JSON output from AI
  • Filter mentions requiring alerts — Routes based on sentiment/urgency thresholds
  • Deduplicate — Removes near-duplicate mentions (e.g. same content reposted)

4. Store, alert & report

  • Log mention to Airtable — Appends/updates records with full details, sentiment, AI analysis, timestamp
  • Route by sentiment and urgency — Critical/negative → immediate action path
  • Send mention alert — Posts formatted message to Slack (or Discord/Teams) with link, text snippet, sentiment badge
  • Generate HTML daily digest report — Compiles summary: total mentions, sentiment breakdown, top issues, trends
  • Email HTML digest — Sends polished report to marketing team via Email node (SMTP/Gmail)
  • Log success and update listings — Records workflow completion, stats for monitoring

Data Sources

  • Twitter/X — Recent search for mentions/keywords (via Twitter node or HTTP Request with API)
  • Reddit — Subreddit or site-wide search for brand mentions
  • News APIs — NewsAPI.org, Google News RSS, or similar for article mentions
  • AI Model — OpenAI (GPT-4o / GPT series), Grok, or other LLM for sentiment/urgency analysis
  • Storage — Airtable base (tables for mentions, daily summaries)
  • Notifications — Slack (webhook or app), Email (SMTP)

How to Use

  1. Import the workflow JSON into your n8n instance
  2. Configure credentials:
    • Twitter/X API (OAuth or Bearer token for search)
    • Reddit API (if using official; or RSS/HTTP for subreddits)
    • News API key (e.g. NewsAPI.org)
    • OpenAI API key (or Grok/other LLM)
    • Airtable API key + base/table
    • Slack webhook or app token
    • Email SMTP credentials
  3. Set monitoring parameters — Edit brand name, keywords, exclude lists in Set monitoring config node
  4. Customize AI prompt — In the AI sentiment node, tweak for brand-specific tone, industry terms, urgency criteria
  5. Adjust schedule — Change interval in Monitor mentions every hour trigger
  6. Tune filters — Set thresholds for alerts (e.g. only negative + high urgency)
  7. Test manually — Use Execute Workflow to simulate with known mentions
  8. Activate — Turn on and watch Executions + Airtable/Slack for results

Requirements

  • n8n instance (self-hosted or cloud)
  • API access/keys for Twitter/X, Reddit (optional), News source
  • OpenAI (or compatible LLM) API key with good token limit
  • Airtable workspace/base for logging
  • Slack workspace for alerts
  • Email account for daily digests

Customizing This Workflow

  • Add more platforms — Include Facebook/Instagram (via Meta API), LinkedIn, Discord mentions
  • Enhance AI analysis — Add topic clustering, competitor comparison, virality scoring
  • Improve deduplication — Use fuzzy matching or embeddings for better duplicate detection
  • Visual dashboard — Export Airtable data to Google Looker Studio / Grafana for sentiment trends
  • Auto-response — For low-risk positive mentions, generate draft replies
  • Language support — Add multilingual sentiment detection
  • Hourly vs. real-time — Switch to webhook triggers if platforms support (e.g. Twitter webhooks if available)
  • Daily/weekly reports — Aggregate more stats, charts in HTML email